With the developments and applications of wireless communications, more and more applications require advanced radio transmission technology (RTT) to reach the goal of low-power, high spectrum efficiency and flexible to multiple scenarios such as mobile broadband, ultra reliable communications, internet-of-things. Recently intelligent optimization and self-learning algorithms are widely studied. Evolution algorithm is to find maximum point with complex non-continuous cost functions by biologic technology such as genetic algorithm and particle swarm optimization. Self-learning algorithm is lighted up with the success of machine-learning in artificial intelligent field. With the strong requirements to RTT and fruitful achievements in evolution and self-learning algorithm (ESLA), it is foreseen that applying ESLA to RTT may help solve some challenges in wireless communications.
This workshop will provide a forum for both industry and academia to exchange views and visions. Topics of interest include but are not limited to the following:
• Overview of intelligent optimization
• Overview of machine-learning algorithms
• Massive MIMO with ESLA
• Position/location estimation with ESLA
• Radio resource management with ESLA
• Signal detection with ESLA
• Channel estimation and tracking with ESLA
• Channel coding and decoding with ESLA
• Power control with ESLA
Important Dates
Paper Submission:
Acceptance Notification:
Camera-Ready:
Workshop: |
July 27, 2017
August 11, 2017
August 18, 2017
October 10, 2017 |
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